Abstract
BackgroundHorizontal gene transfer contributes to bacterial evolution through mobilising genes across various taxonomical boundaries. It is frequently mediated by mobile genetic elements (MGEs), which may capture, maintain, and rearrange mobile genes and co-mobilise them between bacteria, causing horizontal gene co-transfer (HGcoT). This physical linkage between mobile genes poses a great threat to public health as it facilitates dissemination and co-selection of clinically important genes amongst bacteria. Although rapid accumulation of bacterial whole-genome sequencing data since the 2000s enables study of HGcoT at the population level, results based on genetic co-occurrence counts and simple association tests are usually confounded by bacterial population structure when sampled bacteria belong to the same species, leading to spurious conclusions.ResultsWe have developed a network approach to explore WGS data for evidence of intraspecies HGcoT and have implemented it in R package GeneMates (github.com/wanyuac/GeneMates). The package takes as input an allelic presence-absence matrix of interested genes and a matrix of core-genome single-nucleotide polymorphisms, performs association tests with linear mixed models controlled for population structure, produces a network of significantly associated alleles, and identifies clusters within the network as plausible co-transferred alleles. GeneMates users may choose to score consistency of allelic physical distances measured in genome assemblies using a novel approach we have developed and overlay scores to the network for further evidence of HGcoT. Validation studies of GeneMates on known acquired antimicrobial resistance genes in Escherichia coli and Salmonella Typhimurium show advantages of our network approach over simple association analysis: (1) distinguishing between allelic co-occurrence driven by HGcoT and that driven by clonal reproduction, (2) evaluating effects of population structure on allelic co-occurrence, and (3) direct links between allele clusters in the network and MGEs when physical distances are incorporated.ConclusionGeneMates offers an effective approach to detection of intraspecies HGcoT using WGS data.
Highlights
Horizontal gene transfer contributes to bacterial evolution through mobilising genes across various taxonomical boundaries
Since bacteria reproduce asexually and Horizontal gene transfer (HGT) can occur across different levels of taxonomic boundaries [2], gene-gene associations that cannot be completely explained by bacterial population structure suggests horizontal gene co-transfer (HGcoT) [8]
We assessed the performance of GeneMates and validated our methodology using published whole-genome sequencing (WGS) data sets of two bacterial pathogens of great clinical concern: multidrugresistant E. coli and S. enterica serovar Typhimurium
Summary
We assessed the performance of GeneMates and validated our methodology using published WGS data sets of two bacterial pathogens of great clinical concern: multidrugresistant E. coli and S. enterica serovar Typhimurium. Reasons for inconsistency in measured physical distances In both the E. coli and Salmonella data sets, a lack of consistency in SPDs (namely, c = 0) measured between several positively associated alleles of acquired AMR genes was observed (Tables s10 and s11) We investigated this issue based on GeneMates outputs and identified two common explanations. The second set of positive controls for validation consisted of five AMR genes (aadA2, floR, tet(G), blaCARB-2, and sul1) that are co-localised in the acquired multidrug-resistant element SGI1 in Salmonella genomes [20] For these genes, LMMs and PLMs identified significant positive associations between eight and ten allele pairs, respectively (Table 2). The first clique consisted of alleles dfrA1, aadA1pm.181, and sat-2A detected in E. coli genomes Between these alleles, LMMs identified significant positive associations (Figure s18a), and SPDs (Table s12) showed complete identity as well as perfect measurability (namely, sd = 1 for every edge of this clique). This MDR region was shared by a great variety of plasmids
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